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MCP OpenAI Tools

by evandavid1
GitHub
Python
MIT License
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MCP OpenAI Tools

A Model Context Protocol (MCP) server that provides access to OpenAI's advanced models (including o3) with web search, code interpreter, and combined analysis capabilities.

Features

  • Web Search: Search the web using OpenAI's integrated web search capability

  • Code Interpreter: Execute Python code in OpenAI's sandboxed environment

  • Search & Analyze: Combine web search with code analysis in a single operation

  • Direct Prompting: Send prompts directly to OpenAI models with optional web search

  • Health Check: Monitor server status and configuration

  • Configurable Reasoning: Adjust reasoning effort levels (low, medium, high) for optimal performance

Prerequisites

  • Python 3.11 or higher

  • OpenAI API key with access to o3 or other supported models

  • uv package manager (recommended) or pip

Installation

Option 1: Install from Source (Recommended for Development)

  1. Clone the repository:

git clone https://github.com/evandavid1/mcp-openai-tools.git cd mcp-openai-tools

  1. Create a virtual environment and install dependencies:

# Using uv (recommended) uv venv uv pip install -e . # Or using pip python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate pip install -e .

Option 2: Install as a Dependency in Your Project

# Using uv uv add /path/to/mcp-openai-tools # Or using pip pip install /path/to/mcp-openai-tools

Configuration

1. Set up your API Key

Create a .env file in your project root (not in the mcp-openai-tools directory):

OPENAI_API_KEY=your-api-key-here OPENAI_MODEL=o3 # Optional, defaults to gpt-5

Security Note: Never commit your .env file to version control. Add it to your .gitignore.

2. Configure MCP Server

Add the mcp-openai-tools server to your .mcp.json configuration:

For Local Development:

{ "mcpServers": { "mcp-openai-tools": { "type": "stdio", "command": "/path/to/mcp-openai-tools/.venv/bin/python", "args": ["-m", "mcp_openai_tools.main"], "cwd": "/path/to/your/project", "env": { "OPENAI_MODEL": "o3" } } } }

For Installed Package:

{ "mcpServers": { "mcp-openai-tools": { "type": "stdio", "command": "python", "args": ["-m", "mcp_openai_tools.main"], "cwd": "/path/to/your/project", "env": { "PYTHONPATH": "/path/to/mcp-openai-tools/src", "OPENAI_MODEL": "o3" } } } }

3. Environment Variable Options

The server supports multiple ways to specify the .env file location:

  • Default: Looks for .env in the current working directory

  • Parent Directories: Searches up to 3 parent directories

  • Custom Path: Set ENV_FILE environment variable to specify a custom path:

    "env": { "ENV_FILE": "/custom/path/to/.env", "OPENAI_MODEL": "o3" }

Usage

Available Tools

Once configured, the following tools are available in your MCP client (e.g., Claude Code):

  1. openai_web_search: Search the web for current information

    Parameters: - query: Search query string - reasoning_effort: "low" | "medium" | "high" (default: "medium") - model: Optional model override

  2. openai_code_interpreter: Execute Python code in a sandboxed environment

    Parameters: - instruction: What to do with the code - code: Optional Python code (generated if not provided) - reasoning_effort: "low" | "medium" | "high" (default: "medium") - model: Optional model override

  3. openai_search_and_analyze: Combine web search with code analysis

    Parameters: - task: Description of what to search and analyze - reasoning_effort: "low" | "medium" | "high" (default: "medium") - model: Optional model override

  4. openai_prompt: Direct prompting with optional web search

    Parameters: - text: Prompt text - reasoning_effort: "low" | "medium" | "high" (default: "medium") - model: Optional model override - include_web_search: Enable web search (default: true)

  5. openai_health_check: Check server status and configuration

    Parameters: None

Example Usage in Claude Code

# Web search example result = openai_web_search( query="latest developments in quantum computing 2024", reasoning_effort="high" ) # Code interpreter example result = openai_code_interpreter( instruction="Create a visualization of fibonacci sequence growth", code="import matplotlib.pyplot as plt\n# Generate fibonacci...", reasoning_effort="medium" ) # Combined search and analysis result = openai_search_and_analyze( task="Find current S&P 500 data and create a performance chart", reasoning_effort="high" )

Troubleshooting

Common Issues

  1. "OPENAI_API_KEY environment variable is not set"

    • Ensure your .env file exists and contains OPENAI_API_KEY=your-key

    • Check that the working directory (cwd) in .mcp.json points to your project directory

    • Try setting ENV_FILE environment variable to the absolute path of your .env file

  2. "No .env file found. Using system environment variables only"

    • This warning appears when no .env file is found but may still work if you've set environment variables in your system

    • Check the server logs to see which directories were searched

  3. Module not found errors

    • Ensure PYTHONPATH is set correctly in .mcp.json if using the package from another location

    • Verify the virtual environment is activated if running locally

  4. API errors or model access issues

    • Verify your API key has access to the specified model (o3, gpt-5, etc.)

    • Check OpenAI API status and your account limits

Debugging

Enable detailed logging by checking the server output. The server logs:

  • Where it's looking for .env files

  • Which .env file was loaded (if any)

  • API configuration status

  • Tool execution details

Development

Running Tests

# Using pytest pytest tests/ # With coverage pytest tests/ --cov=mcp_openai_tools

Project Structure

mcp-openai-tools/ ├── src/ │ └── mcp_openai_tools/ │ ├── __init__.py │ ├── main.py # Entry point │ ├── server.py # MCP server setup │ ├── core/ │ │ ├── config.py # Configuration management │ │ └── client.py # OpenAI client setup │ ├── tools/ │ │ ├── web_search.py │ │ ├── code_interpreter.py │ │ ├── search_analyze.py │ │ ├── prompt.py │ │ └── health_check.py │ └── prompts/ │ └── user_prompts.py ├── tests/ ├── .env.example # Example environment file ├── .mcp.json.example # MCP configuration example ├── pyproject.toml # Package configuration └── README.md # This file

Contributing

Contributions are welcome! Please:

  1. Fork the repository

  2. Create a feature branch

  3. Make your changes with tests

  4. Submit a pull request

License

MIT License - see LICENSE file for details

Support

For issues, questions, or suggestions:

  • Open an issue on GitHub

  • Check existing issues for solutions

  • Review the server logs for debugging information

This server cannot be installed

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security - not tested
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license - not tested
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quality - not tested

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Provides access to OpenAI's advanced models (including o3) with integrated web search, Python code interpreter, and combined analysis capabilities. Enables users to perform web searches, execute code in sandboxed environments, and combine search with analysis through natural language.

  1. Features
    1. Prerequisites
      1. Installation
        1. Option 1: Install from Source (Recommended for Development)
        2. Option 2: Install as a Dependency in Your Project
      2. Configuration
        1. 1. Set up your API Key
        2. 2. Configure MCP Server
        3. 3. Environment Variable Options
      3. Usage
        1. Available Tools
        2. Example Usage in Claude Code
      4. Troubleshooting
        1. Common Issues
        2. Debugging
      5. Development
        1. Running Tests
        2. Project Structure
      6. Contributing
        1. License
          1. Support

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